Task-Based Ontology for Information Systems

Problem solving method describes the reasoning process and knowledge requirement for accomplishing a given task. There are a number of problems solving methods and other problem solving approaches currently in place. Apparently, these existing approaches demonstrate an excellent work done in the field. Several of these approaches are technology based or driven where the designer/developer has to force fit their design into these technologies. Further, it is not clear as to how such approaches account for external representations in problem solving, epistemological limitations that humans and computers have, and pragmatic constraints associated with real world problems. In this paper we have examined these perspectives and taken them into account for developing Task-Based Problem Solving Adapters (TPSAs). TPSAs developed by us lead toward human centeredness and help us to address the pragmatic task constraints through a range of technologies like neural networks, fuzzy logic, and genetic algorithms. We have also provided an example of applying the TPSAs to develop a working system for assisting sales engineers of an electrical manufacturing firm in monitoring the status of orders in the company

A framework for knowledge discovery within business intelligence for decision support

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Business Intelligence (BI) techniques provide the potential to not only efficiently manage but further analyse and apply the collected information in an effective manner. Benefiting from research both within industry and academia, BI provides functionality for accessing, cleansing, transforming, analysing and reporting organisational datasets. This provides further opportunities for the data to be explored and assist organisations in the discovery of correlations, trends and patterns that exist hidden within the data. This hidden information can be employed to provide an insight into opportunities to make an organisation more competitive by allowing manager to make more informed decisions and as a result, corporate resources optimally utilised. This potential insight provides organisations with an unrivalled opportunity to remain abreast of market trends. Consequently, BI techniques provide significant opportunity for integration with Decision Support Systems (DSS). The gap which was identified within the current body of knowledge and motivated this research, revealed that currently no suitable framework for BI, which can be applied at a meta-level and is therefore tool, technology and domain independent, currently exists. To address the identified gap this study proposes a meta-level framework: - ‘KDDS-BI’, which can be applied at an abstract level and therefore structure a BI investigation, irrespective of the end user. KDDS-BI not only facilitates the selection of suitable techniques for BI investigations, reducing the reliance upon ad-hoc investigative approaches which rely upon ‘trial and error’, yet further integrates Knowledge Management (KM) principles to ensure the retention and transfer of knowledge due to a structured approach to provide DSS that are based upon the principles of BI. In order to evaluate and validate the framework, KDDS-BI has been investigated through three distinct case studies. First KDDS-BI facilitates the integration of BI within ‘Direct Marketing’ to provide innovative solutions for analysis based upon the most suitable BI technique. Secondly, KDDS-BI is investigated within sales promotion, to facilitate the selection of tools and techniques for more focused in store marketing campaigns and increase revenue through the discovery of hidden data, and finally, operations management is analysed within a highly dynamic and unstructured environment of the London Underground Ltd. network through unique a BI solution to organise and manage resources, thereby increasing the efficiency of business processes. The three case studies provide insight into not only how KDDS-BI provides structure to the integration of BI within business process, but additionally the opportunity to analyse the performance of KDDS-BI within three independent environments for distinct purposes provided structure through KDDS-BI thereby validating and corroborating the proposed framework and adding value to business processes

Ubiquitous Computing

The aim of this book is to give a treatment of the actively developed domain of Ubiquitous computing. Originally proposed by Mark D. Weiser, the concept of Ubiquitous computing enables a real-time global sensing, context-aware informational retrieval, multi-modal interaction with the user and enhanced visualization capabilities. In effect, Ubiquitous computing environments give extremely new and futuristic abilities to look at and interact with our habitat at any time and from anywhere. In that domain, researchers are confronted with many foundational, technological and engineering issues which were not known before. Detailed cross-disciplinary coverage of these issues is really needed today for further progress and widening of application range. This book collects twelve original works of researchers from eleven countries, which are clustered into four sections: Foundations, Security and Privacy, Integration and Middleware, Practical Applications

Reconfigurable web service integration in the extended logistics enterprise

Transportation and warehousing logistics are activities that require strong information systems and computer support. This requirement has grown with the advent of e-commerce. Companies such as FedEx and UPS now allow their customers to track and monitor the fulfilment of their requested services on the Internet. In order for such a system to be effective, the goods need to be handled by the one corporation, with an integrated system. This is rare in the case of Small to Medium sized Enterprise (SME). With the advent of Business to Business (B2B), and Partner to Partner (P2P) e-commerce, there has been an increasing tendency for SMEs to set up consortia that represent several players in a given field in order to contend with larger competitors. This paper deals with the concept of an extended logistics enterprise and explores the software engineering issues underlying the development of such complex systems

HIDE: User centred Domotic evolution toward Ambient Intelligence

Pervasive Computing and Ambient Intelligence (AmI) visions are still far from being achieved, especially with regard to Domotics and home applications. According to the vision of Ambient Intelligence (AmI), the most advanced technologies are those that disappear: at maturity, computer technology should become invisible. All the objects surrounding us must possess sufficient computing capacity to interact with users, the surroundings and each other. The entire physical environment in which users are immersed should thus be a hidden computer system equipped with the appropriate software in order to exhibit intelligent behavior. Even though many implementations have started to appear in several contexts, few applications have been made available for the home environment and the general public. This is mainly due to the segmentation of standards and proprietary solutions, which are currently confusing the market with a sparse offer of uninteroperable devices and systems. Although modern houses are equipped with smart technological appliances, still very few of these appliances can be seamlessly connected to each other. The objective of this research work is to take steps in these directions by proposing, on the one hand, a software system designed to make today’s heterogeneous, mostly incompatible domotic systems fully interoperable and, on the other hand, a feasible software application able to learn the behavior and habits of home inhabitants in order to actively contribute to anticipating user needs, and preventing emergency situations for his health. By applying machine learning techniques, the system offers a complete, ready-to-use practical application that learns through interaction with the user in order to improve life quality in a technological living environment, such as a house, a smart city and so on. The proposed solution, besides making life more comfortable for users without particular needs, represents an opportunity to provide greater autonomy and safety to disabled and elderly occupants, especially the critically ill ones. The prototype has been developed and is currently running at the Pisa CNR laboratory, where a home environment has been faithfully recreated

Integration of e-business strategy for multi-lifecycle production systems

Internet use has grown exponentially on the last few years becoming a global communication and business resource. Internet-based business, or e-Business will truly affect every sector of the economy in ways that today we can only imagine. The manufacturing sector will be at the forefront of this change. This doctoral dissertation provides a scientific framework and a set of novel decision support tools for evaluating, modeling, and optimizing the overall performance of e-Business integrated multi-lifecycle production systems. The characteristics of this framework include environmental lifecycle study, environmental performance metrics, hyper-network model of integrated e-supply chain networks, fuzzy multi-objective optimization method, discrete-event simulation approach, and scalable enterprise environmental management system design. The dissertation research reveals that integration of e-Business strategy into production systems can alter current industry practices along a pathway towards sustainability, enhancing resource productivity, improving cost efficiencies and reducing lifecycle environmental impacts. The following research challenges and scholarly accomplishments have been addressed in this dissertation: Identification and analysis of environmental impacts of e-Business. A pioneering environmental lifecycle study on the impact of e-Business is conducted, and fuzzy decision theory is further applied to evaluate e-Business scenarios in order to overcome data uncertainty and information gaps; Understanding, evaluation, and development of environmental performance metrics. Major environmental performance metrics are compared and evaluated. A universal target-based performance metric, developed jointly with a team of industry and university researchers, is evaluated, implemented, and utilized in the methodology framework; Generic framework of integrated e-supply chain network. The framework is based on the most recent research on large complex supply chain network model, but extended to integrate demanufacturers, recyclers, and resellers as supply chain partners. Moreover, The e-Business information network is modeled as a overlaid hypernetwork layer for the supply chain; Fuzzy multi-objective optimization theory and discrete-event simulation methods. The solution methods deal with overall system parameter trade-offs, partner selections, and sustainable decision-making; Architecture design for scalable enterprise environmental management system. This novel system is designed and deployed using knowledge-based ontology theory, and XML techniques within an agent-based structure. The implementation model and system prototype are also provided. The new methodology and framework have the potential of being widely used in system analysis, design and implementation of e-Business enabled engineering systems

A framework for knowledge discovery within business intelligence for decision support

Business Intelligence (BI) techniques provide the potential to not only efficiently manage but further analyse and apply the collected information in an effective manner. Benefiting from research both within industry and academia, BI provides functionality for accessing, cleansing, transforming, analysing and reporting organisational datasets. This provides further opportunities for the data to be explored and assist organisations in the discovery of correlations, trends and patterns that exist hidden within the data. This hidden information can be employed to provide an insight into opportunities to make an organisation more competitive by allowing manager to make more informed decisions and as a result, corporate resources optimally utilised. This potential insight provides organisations with an unrivalled opportunity to remain abreast of market trends. Consequently, BI techniques provide significant opportunity for integration with Decision Support Systems (DSS). The gap which was identified within the current body of knowledge and motivated this research, revealed that currently no suitable framework for BI, which can be applied at a meta-level and is therefore tool, technology and domain independent, currently exists. To address the identified gap this study proposes a meta-level framework: - ‘KDDS-BI’, which can be applied at an abstract level and therefore structure a BI investigation, irrespective of the end user. KDDS-BI not only facilitates the selection of suitable techniques for BI investigations, reducing the reliance upon ad-hoc investigative approaches which rely upon ‘trial and error’, yet further integrates Knowledge Management (KM) principles to ensure the retention and transfer of knowledge due to a structured approach to provide DSS that are based upon the principles of BI. In order to evaluate and validate the framework, KDDS-BI has been investigated through three distinct case studies. First KDDS-BI facilitates the integration of BI within ‘Direct Marketing’ to provide innovative solutions for analysis based upon the most suitable BI technique. Secondly, KDDS-BI is investigated within sales promotion, to facilitate the selection of tools and techniques for more focused in store marketing campaigns and increase revenue through the discovery of hidden data, and finally, operations management is analysed within a highly dynamic and unstructured environment of the London Underground Ltd. network through unique a BI solution to organise and manage resources, thereby increasing the efficiency of business processes. The three case studies provide insight into not only how KDDS-BI provides structure to the integration of BI within business process, but additionally the opportunity to analyse the performance of KDDS-BI within three independent environments for distinct purposes provided structure through KDDS-BI thereby validating and corroborating the proposed framework and adding value to business processes.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse